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On the use of heterogeneous thresholds ordinal regression models to account for individual differences in response style

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  • Timothy Johnson

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  • Timothy Johnson, 2003. "On the use of heterogeneous thresholds ordinal regression models to account for individual differences in response style," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 563-583, December.
    • Handle: RePEc:spr:psycho:v:68:y:2003:i:4:p:563-583
    DOI: 10.1007/BF02295612
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    References listed on IDEAS

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    1. Rossi P. E & Gilula Z. & Allenby G. M, 2001. "Overcoming Scale Usage Heterogeneity: A Bayesian Hierarchical Approach," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 20-31, March.
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    Cited by:

    1. Anne Thissen-Roe & David Thissen, 2013. "A Two-Decision Model for Responses to Likert-Type Items," Journal of Educational and Behavioral Statistics, , vol. 38(5), pages 522-547, October.
    2. Jay Verkuilen & Michael Smithson, 2012. "Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution," Journal of Educational and Behavioral Statistics, , vol. 37(1), pages 82-113, February.
    3. Gerhard Tutz, 2021. "Hierarchical Models for the Analysis of Likert Scales in Regression and Item Response Analysis," International Statistical Review, International Statistical Institute, vol. 89(1), pages 18-35, April.
    4. Nino Hardt & Alex Varbanov & Greg M. Allenby, 2016. "Monetizing Ratings Data for Product Research," Marketing Science, INFORMS, vol. 35(5), pages 713-726, September.
    5. Gerhard Tutz, 2020. "Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice model," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(3), pages 517-542, September.
    6. Bettina Grün & Sara Dolnicar, 2016. "Response style corrected market segmentation for ordinal data," Marketing Letters, Springer, vol. 27(4), pages 729-741, December.
    7. Martijn Jong & Jan-Benedict Steenkamp, 2010. "Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 3-32, March.
    8. Timothy R. Johnson & Daniel M. Bolt, 2010. "On the Use of Factor-Analytic Multinomial Logit Item Response Models to Account for Individual Differences in Response Style," Journal of Educational and Behavioral Statistics, , vol. 35(1), pages 92-114, February.
    9. Rosaria Simone & Gerhard Tutz, 2018. "Modelling uncertainty and response styles in ordinal data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 224-245, August.
    10. Omori, Yasuhiro & Miyawaki, Koji, 2010. "Tobit model with covariate dependent thresholds," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2736-2752, November.
    11. Fang Liu & Xiaojing Wang & Roeland Hancock & Ming-Hui Chen, 2022. "Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1290-1317, December.
    12. Pieter Schoonees & Michel Velden & Patrick Groenen, 2015. "Constrained Dual Scaling for Detecting Response Styles in Categorical Data," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 968-994, December.
    13. Gerhard Tutz & Moritz Berger, 2016. "Response Styles in Rating Scales," Journal of Educational and Behavioral Statistics, , vol. 41(3), pages 239-268, June.
    14. Lynd Bacon & Peter Lenk, 2012. "Augmenting discrete-choice data to identify common preference scales for inter-subject analyses," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 453-474, December.
    15. de Jong, M.G., 2006. "Response bias in international marketing research," Other publications TiSEM 5d4031be-97b5-4db3-962b-2, Tilburg University, School of Economics and Management.
    16. Roberto Colombi & Sabrina Giordano & Gerhard Tutz, 2021. "A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories," Journal of Educational and Behavioral Statistics, , vol. 46(6), pages 682-716, December.
    17. Dirk Lubbe & Christof Schuster, 2020. "A Scaled Threshold Model for Measuring Extreme Response Style," Journal of Educational and Behavioral Statistics, , vol. 45(1), pages 86-107, February.
    18. Timothy Johnson, 2007. "Discrete Choice Models for Ordinal Response Variables: A Generalization of the Stereotype Model," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 489-504, December.
    19. Kim, Jung Seek & Ratchford, Brian T., 2013. "A Bayesian multivariate probit for ordinal data with semiparametric random-effects," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 192-208.

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